The Development and Validation of a Nomogram for Predicting Poor Recovery in Cardiac Surgery Patients Using the Quality of Recovery-15 (QoR-15) Score

Background: Multiple risk factors may contribute to adverse postoperative outcomes in cardiac surgery. This study sought to develop a nomogram for predicting poor recovery in cardiac surgery patients based on the patient-reported global score of the 15-item Quality of Recovery (QoR-15) scale. Methods: A retrospective study was conducted involving adult patients who underwent cardiac surgery from July 2023 to July 2024. Data collected included demographics, clinical variables, and surgical details. Poor recovery was defined as a QoR-15 score less than 118 at 24 hours post-operation. Significant predictors of poor recovery were identified through multivariate logistic regression analysis and were used to develop a nomogram. The model's performance was evaluated using the area under the curve (AUC) and calibration plots. Results: Of the 1768 patients included, the incidence of poor recovery was 27.6%. Key predictors of poor recovery included age, gender, hypertension, diabetes, operation duration, cardiopulmonary bypass duration, intraoperative blood loss, ejection fraction, and the use of dexmedetomidine administration (p < 0.05). The nomogram showed a strong discriminative capability, with an AUC of 0.795 in the training dataset and 0.734 in the testing dataset. Calibration plots indicated a high level of consistency between predicted and actual probabilities. Conclusion: The nomogram effectively predicts a QoR-15 score <118 in patients 24 hours after cardiac surgery and can be useful in forecasting poor recovery.